# metric.ldata

##### Distance Matrix Computation for ldata and mfdata class object

This function computes the distances between the list elements
This function returns a distance matrix by using `metric.lp`

function for `fdata`

objects and `metric.dist`

function for `vector`

and `matric`

objects.

- Keywords
- cluster

##### Usage

```
metric.ldata(
ldata1,
ldata2 = NULL,
include = "all",
exclude = "none",
metric,
par.metric = NULL,
w,
method = "none"
)
```

##### Arguments

- ldata1
List with of fdata objects and a data.frame object calle 'df'.

- ldata2
List with of fdata objects and a data.frame object calle 'df'.

- include
vector with the name of variables to use

- exclude
vector with the name of variables to not use

- metric
Type of metric to combine, if 'none', the function no combine and return a list o distances for each variable included

- par.metric
List of metric parameters for each variable included

- w,
weights to combine the metric (if metric is not 'none')

- method
The distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski".

- …
Further arguments passed to

`dist`

function.

##### See Also

See also `dist`

for multivariate date case and
`metric.lp for functional data case`

##### Examples

```
# NOT RUN {
data(tecator)
names(tecator)[2]<-"df"
# Example 1 (list of distances)
ldist <- metric.ldata(tecator,method="none")
lapply(ldist,names)
# Example 2 (combined metric)
mdist <- metric.ldata(tecator,method="euclidean")
dim(mdist)
# }
```

*Documentation reproduced from package fda.usc, version 2.0.1, License: GPL-2*